Poisoning Attacks and Defenses to Federated Unlearning

Machine learning with adversaries: Byzantine tolerant gradient descent. In NeurIPS

Peva Blanchard, El Mahdi El Mhamdi, Rachid Guerraoui, and Julien Stainer. 2017 · 2017

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Communication-Efficient Learning of Deep Networks from Decentralized Data. In AISTATS

H. Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas. 2017 · 2017

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The hidden vulnerability of distributed learning in byzantium. In ICML

Rachid Guerraoui, Sébastien Rouault, et al · 2018

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Byzantine-robust distributed learning: Towards optimal statistical rates. In ICML

Dong Yin, Yudong Chen, Ramchandran Kannan, and Peter Bartlett. 2018 · 2018

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A little is enough: Circumventing defenses for distributed learning. In NeurIPS

Gilad Baruch, Moran Baruch, and Yoav Goldberg. 2019 · 2019

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How to backdoor federated learning. In AISTATS

Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov. 2020 · 2020

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Local model poisoning attacks to Byzantine-robust federated learning. In USENIX Security Symposium

Minghong Fang, Xiaoyu Cao, Jinyuan Jia, and Neil Gong. 2020 · 2020

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Fltrust: Byzantine-robust federated learning via trust bootstrapping. In NDSS

Xiaoyu Cao, Minghong Fang, Jia Liu, and Neil Zhenqiang Gong. 2021 · 2021

Cited alongside, same era.

Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning. In NDSS

Virat Shejwalkar and Amir Houmansadr. 2021 · 2021

Cited alongside, same era.

Aflguard: Byzantine-robust asynchronous federated learning. In ACSAC

Minghong Fang, Jia Liu, Neil Zhenqiang Gong, and Elizabeth S Bentley. 2022 · 2022

Cited alongside, same era.

FLAME: Taming backdoors in federated learning. In USENIX Security Symposium

Thien Duc Nguyen, Phillip Rieger, Roberta De Viti, Huili Chen, Björn B Brandenburg, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, et al · 2022

Cited alongside, same era.

Fedrecover: Recovering from poisoning attacks in federated learning using historical information. In IEEE Symposium on Security and Privacy

Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang, and Neil Zhenqiang Gong. 2023 · 2023

Cited alongside, same era.

Robust Federated Unlearning. In CIKM

Xinyi Sheng, Wei Bao, and Liming Ge. 2024 · 2024

Later among the works it cites.

Communication efficient and provable federated unlearning. In VLDB

Youming Tao, Cheng-Long Wang, Miao Pan, et al · 2024

Later among the works it cites.

FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error. In ICML

Yueqi Xie, Minghong Fang, and Neil Zhenqiang Gong. 2024 · 2024

Later among the works it cites.

Poisoning federated recommender systems with fake users. In The Web Conference

Ming Yin, Yichang Xu, Minghong Fang, and Neil Zhenqiang Gong. 2024 · 2024

Later among the works it cites.

Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction. In IFIP/IEEE Networking Conference

Zifan Zhang, Minghong Fang, Jiayuan Huang, and Yuchen Liu. 2024 · 2024

Later among the works it cites.